Presentation
12 August 2023 Virtually stained H&E images and nuclei segmentation combining neural networks and spectral phasor analysis
Elena Pagani, Davide Panzeri, Riccardo Scodellaro, Margaux Bouzin, Laura D'Alfonso, Maddalena Collini, Giuseppe Chirico, Donato Inverso, Laura Sironi
Author Affiliations +
Abstract
H&E stained sections are the gold standard for disease diagnosis but, unfortunately, the staining process is time-consuming and expensive. In an effort to overcome these problems, here, we propose a virtual staining algorithm, able to predict an Hematoxylin/Eosin (H&E) image, usually exploited during clinical evaluations, starting from the autofluorescence signal of entire liver tissue sections acquired by a confocal microscope. The color and texture contents of the generated virtually stained images have been analyzed through the phasor-based approach to detect tumorous tissue and to segment relevant biological structures (accuracy>90% compared to the expert manual analysis).
Conference Presentation
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Elena Pagani, Davide Panzeri, Riccardo Scodellaro, Margaux Bouzin, Laura D'Alfonso, Maddalena Collini, Giuseppe Chirico, Donato Inverso, and Laura Sironi "Virtually stained H&E images and nuclei segmentation combining neural networks and spectral phasor analysis", Proc. SPIE PC12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, PC126220J (12 August 2023); https://doi.org/10.1117/12.2673774
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KEYWORDS
Image segmentation

Biological research

Neural networks

Nervous system

Microscopes

Image analysis

Liver

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